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Record W3085284778 · doi:10.1177/1741143220957331

Job demands amid work intensity: British Columbia school administrators’ perceptions

2020· article· en· W3085284778 on OpenAlexaboutno aff
Fei Wang

Bibliographic record

VenueEducational Management Administration & Leadership · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Job shadowJob analysisJob designJob attitudeJob performancePerceptionPublic relationsJob controlJob securityPsychologyJob satisfactionSocial psychologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Job demands overburden school administrators’ personal and professional capacity and affect their performance and well-being. However, studies on principals and vice-principals’ work intensification fail to highlight how their work demands and challenges are manifested, and how work demands contribute to the changing nature of their work. This qualitative study explores in what ways job demands are manifested in school administers’ intensified work conditions and how their perceptions of job demands help them create a sense of control. The study utilizes the job demands model as a framework to help closely examine two types of job demands: job challenges; and job hindrances though principals’ accounts. The results show that job challenges tend to be transitory and are more likely to be overcome; job hindrances however tend to be more institutional and less temporary and harder to overcome. Attempting to deal with job challenges the same as dealing with job hindrances may become challenging itself and build up rather than alleviate work-related stress among school principals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.443

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.255
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2020
Admission routes1
Has abstractyes

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